PhD Studentship in Machine learning for sustainable chemistry in UK 2022

In the academic year 2022/23, the University of Nottingham in the United Kingdom is accepting applications for a PhD Studentship in Machine Learning for Sustainable Chemistry.

Details about the project

This project will concentrate on the creation of novel interpretable and interactive machine learning models as well as data-driven methodologies for projecting consensus green chemistry metrics, allowing researchers to conduct logical evaluations of various chemical synthesis pathways using AI.

Jonathan Hirst will manage the initiative, which is part of a large new Royal Academy of Engineering Chairs in Emerging Technologies program.

Through the EPSRC-funded Prosperity Partnership “Accelerated Discovery and Development of New Medicines: Prosperity Partnership for a Healthier Nation” and the Centre for Doctoral Training (CDT) in “Sustainable Chemistry: Atoms-2-Products an Integrated Approach to Sustainable Chemistry,” the project will involve close collaboration with a range of synthetic chemists with a specific focus on green and sustainable chemistry.

The project will teach a diverse set of skills in computer programming, as well as the creation and use of machine learning methods in chemistry.

Worth of Scholarship

The studentship is fully financed for the whole 36-month period. The RCUK stipend (currently £15,609 per year) will be paid, and tuition fees will be paid at the UK rate.
International students will be responsible for the difference in fees between the UK and the rest of the world.

Requirements for the PhD Studentship in Machine learning for sustainable chemistry

  • Applicants should have, or expect to earn, a 2:1 Honours degree in Chemistry or a related field (or equivalent if from another country). A MChem/MSc-4-year integrated master’s degree, a BSc + MSc, or a BSc with significant research experience would be very beneficial.
  • Computer programming experience is also advantageous.
  • If English is not the candidate’s first language, they must demonstrate that they fulfill the University’s basic English language requirements before commencing the studentship (IELTS 6.0 with at least 5.5 in each element).

How to Apply for the PhD Studentship in Machine learning for sustainable chemistry

To apply, students should first contact Professor Hirst, [email protected], before submitting a formal application via the University’s website.

Application evaluation will begin on Monday, March 14th, 2022, and the post will be filled as soon as a suitable candidate is identified; thus, you are urged to apply as soon as feasible.

For more information and to apply, go here.

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